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Techno-Economic Optimization of Grid-Connected Photovoltaic (PV) and Battery Systems Based on Maximum Demand Reduction (MDRed) Modelling in Malaysia

Author

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  • Gopinath Subramani

    (Centre of Advanced Electrical and Electronic Systems (CAEES), Faculty of Engineering & the Built Environment, Segi University, Kota Damansara, Petaling Jaya 47810, Malaysia)

  • Vigna K. Ramachandaramurthy

    (Institute of Power Engineering, Department of Electrical Power Engineering, College of Engineering, Universiti Tenaga Nasional, Kajang 43000, Malaysia)

  • P. Sanjeevikumar

    (Center for Bioenergy and Green Engineering, Department of Energy Technology, Aalborg University, 6700 Esbjerg, Denmark)

  • Jens Bo Holm-Nielsen

    (Center for Bioenergy and Green Engineering, Department of Energy Technology, Aalborg University, 6700 Esbjerg, Denmark)

  • Frede Blaabjerg

    (Center of Reliable Power Electronics (CORPE), Department of Energy Technology, Aalborg University, 9220 Esbjerg, Denmark)

  • Leonowicz Zbigniew

    (Faculty of Electrical Engineering, Wroclaw University of Science and Technology, Wyb. Wyspianskiego 27, 50370 Wroclaw, Poland)

  • Pawel Kostyla

    (Faculty of Electrical Engineering, Wroclaw University of Science and Technology, Wyb. Wyspianskiego 27, 50370 Wroclaw, Poland)

Abstract

Under the present electricity tariff structure in Malaysia, electricity billing on a monthly basis for commercial and industrial consumers includes the net consumption charges together with maximum demand (MD) charges. The use of batteries in combination with photovoltaic (PV) systems is projected to become a viable solution for energy management, in terms of peak load shaving. Based on the latest studies, maximum demand (MD) reduction can be accomplished via a solar PV-battery system based on a few measures such as load pattern, techno-economic traits, and electricity scheme. Based on these measures, the Maximum Demand Reduction (MDRed) Model is developed as an optimization tool for the solar PV-battery system. This paper shows that energy savings on net consumption and maximum demand can be maximized via optimal sizing of the solar PV-battery system using the MATLAB genetic algorithm (GA) tool. GA optimization results revealed that the optimal sizing of solar PV-battery system gives monthly energy savings of up to 20% of net consumption via solar PV self-consumption, 3% of maximum demand (MD) via MD shaving and 2% of surplus power supplied to grid via net energy metering (NEM) in regards to Malaysian electricity tariff scheme and cost of the overall system.

Suggested Citation

  • Gopinath Subramani & Vigna K. Ramachandaramurthy & P. Sanjeevikumar & Jens Bo Holm-Nielsen & Frede Blaabjerg & Leonowicz Zbigniew & Pawel Kostyla, 2019. "Techno-Economic Optimization of Grid-Connected Photovoltaic (PV) and Battery Systems Based on Maximum Demand Reduction (MDRed) Modelling in Malaysia," Energies, MDPI, vol. 12(18), pages 1-21, September.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:18:p:3531-:d:267109
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    References listed on IDEAS

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    Cited by:

    1. Iflah Javeed & Rahmat Khezri & Amin Mahmoudi & Amirmehdi Yazdani & G. M. Shafiullah, 2021. "Optimal Sizing of Rooftop PV and Battery Storage for Grid-Connected Houses Considering Flat and Time-of-Use Electricity Rates," Energies, MDPI, vol. 14(12), pages 1-19, June.
    2. Mohamed Louzazni & Daniel Tudor Cotfas & Petru Adrian Cotfas, 2020. "Management and Performance Control Analysis of Hybrid Photovoltaic Energy Storage System under Variable Solar Irradiation," Energies, MDPI, vol. 13(12), pages 1-23, June.
    3. Mariusz T. Sarniak, 2020. "Researches of the Impact of the Nominal Power Ratio and Environmental Conditions on the Efficiency of the Photovoltaic System: A Case Study for Poland in Central Europe," Sustainability, MDPI, vol. 12(15), pages 1-15, July.

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